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001032619 0247_ $$2doi$$a10.1137/1.9781611977967.3
001032619 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-06385
001032619 037__ $$aFZJ-2024-06385
001032619 1001_ $$0P:(DE-Juel1)195613$$aMuralikrishnan, Sriramkrishnan$$b0$$eCorresponding author
001032619 1112_ $$aSIAM Conference on Parallel Processing for Scientific Computing$$cBaltimore$$d2024-03-05 - 2024-03-08$$gPP24$$wUSA
001032619 245__ $$aScaling and performance portability of the particle-in-cell scheme for plasma physics applications through mini-apps targeting exascale architectures
001032619 260__ $$aPhiladelphia, PA$$bSociety for Industrial and Applied Mathematics$$c2024
001032619 300__ $$a26-38
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001032619 520__ $$aWe perform a scaling and performance portability study of the electrostatic particle-in-cell scheme for plasma physics applications through a set of mini-apps we name “Alpine”, which can make use of exascale computing capabilities. The mini-apps are based on IPPL, a framework that is designed around performance portable and dimensionality independent particles and fields. We benchmark the simulations with varying parameters, such as grid resolutions ($512^3$ to $2048^3$) and number of simulation particles ($10^9$ to $10^{11}$), with the following mini-apps: weak and strong Landau damping, bump-on-tail and two-stream instabilities, and the dynamics of an electron bunch in a charge-neutral Penning trap. We show strong and weak scaling and analyze the performance of different components on several pre-exascale architectures, such as Piz-Daint, Cori, Summit, and Perlmutter. While the scaling and portability study helps to identify the performance critical components of the particle-in-cell scheme on the current state-of-the-art computing architectures, the mini-apps by themselves can be used to develop new algorithms and optimize their high performance implementations targeting exascale architectures.
001032619 536__ $$0G:(DE-HGF)POF4-5112$$a5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
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001032619 7001_ $$0P:(DE-HGF)0$$aFrey, Matthias$$b1
001032619 7001_ $$0P:(DE-HGF)0$$aVinciguerra, Alessandro$$b2
001032619 7001_ $$0P:(DE-HGF)0$$aLigotino, Michael$$b3
001032619 7001_ $$0P:(DE-HGF)0$$aCerfon, Antoine J.$$b4
001032619 7001_ $$0P:(DE-HGF)0$$aStoyanov, Miroslav$$b5
001032619 7001_ $$0P:(DE-HGF)0$$aGayatri, Rahulkumar$$b6
001032619 7001_ $$0P:(DE-HGF)0$$aAdelmann, Andreas$$b7
001032619 773__ $$a10.1137/1.9781611977967.3
001032619 8564_ $$uhttps://epubs.siam.org/doi/abs/10.1137/1.9781611977967.3
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001032619 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)195613$$aForschungszentrum Jülich$$b0$$kFZJ
001032619 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5112$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001032619 9141_ $$y2024
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